Each operation in your agent can be fine-tuned with advanced settings to control exactly how it functions. These settings help you create more reliable, efficient, and secure agents by controlling data flow and execution behavior.
When you select an operation in the builder interface, you’ll see several configuration tabs that control different aspects of the operation’s behavior:
The Details tab shows the original, generated function calling description that defines the operation’s purpose and behavior. This serves as a reference for the operation’s intended use.
This information is especially useful when you’re working with multiple similar operations and need to understand the exact purpose of each one.
The blue rotating icon in the operation settings allows you to configure how many times an operation can be executed:
You can set operations to:
Execute once: The operation can only be used a single time in a given session (useful for initialization operations)
Execute infinitely: The operation can be used repeatedly as needed (default for most operations)
This setting is particularly important for operations that:
Have rate limits or usage quotas
Should only be performed once per session for logical reasons
Need to be used repeatedly to gather comprehensive data
For example, a search operation might need to run multiple times with different criteria, while a configuration or initialization operation may only need to run once.
When building a LinkedIn researcher agent, you might want to remove personal contact information before passing profile data to the AI:
Select your “Get Profile Data” operation
Click the “Output Schema” tab
Expand the response schema tree
Uncheck fields like emailAddress, phoneNumbers, and other personal fields
Leave professional information like title, company, and skills checked
Save your changes
Now when your agent retrieves profile data, it will only see the professional information without any personal contact details.
If your agent needs to work with a large dataset of company posts:
Select your “Search Posts” operation
Click the “Advanced” tab
Enable “Allow in-context filtering”
Configure which fields should be available for filtering
Save your changes
Now your agent can efficiently search through large post datasets by specifying filtering criteria, and only the relevant posts will be returned, saving significant token usage.
